Small changes make big savings in the Internet of Sensors

TTP’s Steve Taylor argues that the focus should be on the Internet of Sensors (IoS), not the Internet of Things (IoT) and explores the challenges for sensors, from power and size to connectivity and deployment.

While there is a lot of hype around the Internet of Things (IoT), it’s the Internet of Sensors that really matters. Connecting things over the internet is certainly not new. For the last 14 years I have been working on machine to machine (M2M) and even organism to machine applications, from sensors to monitor cow herds, to sensors in orthopaedic joints and F1 engines. In this world, small changes in the sensor map can lead to great gains in the profitability of the machine or health.

The IoT hype is supported by silicon vendors, who are eager to dream up new applications for their chips. In my opinion, that’s putting the cart before horse. Surely, the better way is to look at the needs first and then create systems around them. The IoT is, to a large extent, a solution looking for a problem, rather than the other way round. There’s simply no point in random objects talking to each other just for the sake of it. The IoT only provides the communications backbone. Internet of Sensors (or IoS) looks more like the roots of a tree, with sensors at the bottom feeding data upwards to the trunk – the Internet.

Google has proven the business case for data-mining everything we type, do, say and breathe in order to gain better insight into our lives, actions and needs. Business managers throughout industry want to replicate this with their products, assets and plant. There is a huge amount of data which is not being ‘listened to’ and in heavy industry saving a few percent on energy by improved temperature modelling could be worth billions of pounds.

Certainly, there is a need to pump more data to the cloud to gain greater insight into systems and how they perform in the real world. Knowing this information about industrial applications is extremely valuable, particularly if you can blend local sensor data with historical data.

All fine in theory, but the nitty-gritty detail of implementing these types of systems comes down to issues such as power, data, encapsulation, ease of installation and cost.

In most cases, the primary driver is for a new form of sensing, the rest of the system including power, wireless, data, packaging and enclosure, is only there in support. Some sensors can be pretty exotic. For example, the herd sensor accurately measures the cow’s stomach acidity (pH) for 120 days after calving. Protecting the sensor and electronics is challenging – the stomach contains a cocktail of acid, enzymes, chewed grass, stones and bits of metal ingested by the animal.

Miniature batteries or harvested sources provide tiny amounts of power. However, wireless devices need big gulps of power to convey a radio signal. This can be overcome by reflecting radio signals instead. To ensure reliable data error checking/correction, multiple transmissions at different times, frequencies, codes and locations can be deployed. In many cases such as in F1, batteries simply ‘can’t hack it’ at elevated temperatures, g-force or vibration, so harvesting energy is the only viable solution.

Ubiquitous low-cost sensors are vital to unlock the commercial opportunity. The skill here is in using generic, commodity parts and simple architectures wherever possible. Unique aspects can be hidden in executable software for protection from competitors. The beauty of software is that once written, it’s free to duplicate. If it is kept simple, then hundreds of hours can be saved in development and maintenance.

Often, the requirement for a sensor includes ease of installation or implantation in a machine or living organism. Deployment must be simple and low-cost, with the minimum amount of disturbance to the physical system it is monitoring. Eye implants for example must fit through a mm-scale incision, then self-deploy once inside the eye. Fortunately not everything is this complex.

Connectivity is assumed. The application may need continuous, real-time reporting locally, even when the data or wireless connection can be sporadic. This is tricky, as the algorithms to crunch the data often reside in the Cloud where they can continuously evolve. Instead, a continuously evolving and agile Cloud algorithm is periodically pushed back to the sensor. To make this viable you need hardcore encryption to make sure third parties don’t intercept valuable algorithms or data.

The opportunity

The IoS provides the opportunity to closely monitor and understand how systems and creatures behave in the real world. While the challenges are certainly non-trivial, for ambitious companies that are able to embrace the IoS, there is a real opportunity to take a technological and commercial lead in this rapidly growing market. The race is on, in this brave new world of sensors.